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	Improvement of the example-regression-based super-resolution land cover mapping algorithm
	Zhang, Yihang1,2; Du, Yun1; Ling, Feng1; Li, Xiaodong1
刊名	Ieee geoscience and remote sensing letters
	2015-08-01
卷号	12期号:8页码:1740-1744
关键词	Example based Subpixel mapping (spm) Super-resolution mapping (srm) Support vector regression (svr)
ISSN号	1545-598X
DOI	10.1109/lgrs.2015.2423496
通讯作者	Ling, feng(lingf@whigg.ac.cn)
英文摘要	Super-resolution mapping (srm) is a method for generating a fine-resolution land cover map from coarse-resolution fraction images. example-regression-based srm algorithms can estimate a fine-resolution land cover map with detailed spatial information by learning land cover spatial patterns from available land cover maps. existing example-regression-based srm algorithms are sensitive to fraction errors, and the results often include many linear artifacts and speckles. to overcome these shortcomings, this study proposes an improved example-regression-based srm algorithm. the objective function of the proposed srm algorithm comprises three terms. the first term is used to minimize the difference between the fraction values of the estimated fine-resolution land cover map and the input fraction values. the second term is used to maximize the class membership possibility values of the fine pixels in the result. the final term is used to make the result locally smooth. the proposed srm algorithm is compared with several popular srm algorithms using both synthetic and real fraction images. experimental results indicate that the proposed srm algorithm can produce results with less speckles and linear artifacts, more spatial details, smoother boundaries, and higher accuracies than the srm results used for comparison.
WOS关键词	REMOTELY-SENSED IMAGERY ; NEURAL-NETWORK ; REPRESENTATION ; INFORMATION ; MODEL
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000356542100030
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2376457
专题	中国科学院大学
通讯作者	Ling, Feng
作者单位	1.Chinese Acad Sci, Inst Geodesy & Geophys, Wuhan 430077, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100039, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yihang,Du, Yun,Ling, Feng,et al. Improvement of the example-regression-based super-resolution land cover mapping algorithm[J]. Ieee geoscience and remote sensing letters,2015,12(8):1740-1744.
APA	Zhang, Yihang,Du, Yun,Ling, Feng,&Li, Xiaodong.(2015).Improvement of the example-regression-based super-resolution land cover mapping algorithm.Ieee geoscience and remote sensing letters,12(8),1740-1744.
MLA	Zhang, Yihang,et al."Improvement of the example-regression-based super-resolution land cover mapping algorithm".Ieee geoscience and remote sensing letters 12.8(2015):1740-1744.

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